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Ola Maps: A Homegrown Competitor To Google, Apple Maps

The investment in maps by Ola is "very strategic" and not just a small ingredient, according to Vipul Shah, head of product at Krutrim, who steered the development of the new product.

<div class="paragraphs"><p>(Source: Company blog)</p></div>
(Source: Company blog)

Ola founder Bhavish Aggarwal formally released Ola Maps on Monday, a full-stack in-house map software that had been in the works for three years.

Aggarwal urged Indian developers to give up using Google Maps, about a month after Ola's own exit from Microsoft Azure earlier in the year to its own cloud infrastructure. The Ola Group founder said the move will help save Rs 100 crore annually for the company, which deploys maps across its mobility and electric scooter businesses.

The investment in maps by Ola is "very strategic" and not just a small ingredient, according to Vipul Shah, head of product at Krutrim, who steered the development of the new product.

"It's not just some small capability. It's really the enabler of last-mile mobility. A few years ago, when we were trying to build features in our applications using maps from vendors, we realised India was not really a focus for them," he said.

He added that existing products on the market don't have the nuance of studying traffic patterns, webs of streets and urban landscapes that are unique to India.

Ola's Maps use a combination of crowdsourced information leveraging the existing user base of its electric scooters, open street maps, open source government data repositories and other proprietary sources. The information is curated and cleaned using AI models.

Further, the sensor data generated from two-wheelers, three-wheelers and cars helps in identifying missing roads, real-time traffic congestion and road restrictions, among others.

Shah said that Ola's solution is competitive with any existing solution that's out there, right from day one. He said it is outperforming competition on a few key metrics—location accuracy, search accuracy and latency, and expected time of arrival accuracy.

Location-wise, Ola will use certain points of interest instead of less popular street addresses, resulting in more accurate locations. Calculating ETA, according to Shah, is a very complex algorithm, which is better than competition because of Ola Mobility's vast experience. "It's not just about distances; it's also about traffic patterns and road conditions," he said.

The company's search feature will also be more contextual and the return speed of results will also be faster. "Those two are additional aspects where we are really great. If you put these 3–4 factors together, we've got all the ingredients that matter to our customers," he said.

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